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Machine learning decision support model for discharge planning in stroke patients

Abstract

Background/aim

Efficient discharge for stroke patients is crucial but challenging. The study aimed to develop early predictive models to explore which patient characteristics and variables significantly influence the discharge planning of patients, based on the data available within 24 h of admission.

Design

Prospective observational study.

Methods

A prospective cohort was conducted at a university hospital with 523 patients hospitalised for stroke. We built and trained six different machine learning (ML) models, followed by testing and tuning those models to find the best-suited predictor for discharge disposition, dichotomized into home and non-home. To evaluate the accuracy, reliability and interpretability of the best-performing models, we identified and analysed the features that had the greatest impact on the predictions.

Results

In total, 523 patients met the inclusion criteria, with a mean age of 61 years. Of the patients with stroke, 30.01% had non-home discharge. Our model predicting non-home discharge achieved an area under the receiver operating characteristic curve of 0.95 and a precision of 0.776. After threshold was moved, the model had a recall of 0.809. Top 10 variables by importance were National Institutes of Health Stroke Scale (NIHSS) score, family income, Barthel index (BI) score, FRAIL score, fall risk, pressure injury risk, feeding method, depression, age and dysphagia.

Conclusion

The ML model identified higher NIHSS, BI, and FRAIL, family income, higher fall risk, pressure injury risk, older age, tube feeding, depression and dysphagia as the top 10 strongest risk predictors in identifying patients who required non-home discharge to higher levels of care. Modern ML techniques can support timely and appropriate clinical decision-making.

Relevance to Clinical Practice

This study illustrates the characteristics and risk factors of non-home discharge in patients with stroke, potentially contributing to the improvement of the discharge process.

Reporting Method

STROBE guidelines.

Association between stroke and venous leg ulcers: A Mendelian randomization study

Abstract

To investigate any potential bidirectional causal relationships between stroke and venous leg ulcers (VLUs), Mendelian randomization (MR) analyses were carried out in this study. The exposure factor was stroke, the outcome factor was VLUs. The two-sample MR study was carried out based on the online analysis platform (http://app.mrbase.org/). The association of stroke and VLUs was analysed via methods of Inverse Variance Weighted (IVW), Weighted Median, MR-Egger and weighted mode. IVW method suggested no association between stroke and VLUs ((β 1.06; SE 9.321; p = 0.9095)). Weighted median estimator (β 5.906; SE 11.99, p = 0.6223), MR-Egger (β −0.8677; SE 21.89; p = 0.9691) and weighted mode (β 9.336; SE 17.77; p = 0.6089) showed consistent results. Conversely, evidence indicating that the presence of VLUs increased the risk of stroke was lacking. According to this MR study, there is no causal connection between stroke and VLUs, which suggests that therapies targeting stroke may not be effective against VLUs.

Multicenter effect analysis of one‐step acellular dermis combined with autologous ultra‐thin split thickness skin composite transplantation in treating burn and traumatic wounds

Abstract

To evaluate the efficacy of one-step acellular dermis combined with autologous split thickness skin grafting in the treatment of burn or trauma wounds by a multicenter controlled study. In patients with extensive burns, it is even difficult to repair the wounds due to the shortage of autologous skin. The traditional skin grafting method has the disadvantages of large damage to the donor site, insufficient skin source and unsatisfactory appearance, wear resistance and elasticity of the wound tissue after skin grafting. One-step acellular dermis combined with autologous ultra-thin split thickness skin graft can achieve better healing effect in the treatment of burn and trauma wounds. A total of 1208 patients who underwent single-layer skin grafting and one-step composite skin grafting in the First Affiliated Hospital of Wannan Medical College, Wuhan Third People's Hospital and Lu ‘an People's Hospital from 2019 to 2022 were retrospectively analysed. The total hospitalization cost, total operation cost, hospitalization days after surgery, wound healing rate after 1 week of skin grafting and scar follow-up at 6 months after discharge were compared and studied. The total cost of hospitalization and operation in the composite skin grafting group was significantly higher than those in the single-layer autologous skin grafting group. The wound healing rate after 1 week of skin grafting and the VSS score of scar in the follow-up of 6 months after discharge were better than those in the single-layer skin grafting group. One-step acellular dermis combined with autologous ultra-thin split thickness skin graft has high wound healing rate, less scar, smooth appearance and good elasticity in repairing burn and trauma wounds, which can provide an ideal repair method for wounds.

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